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Data X:
2.26. 1.45. 2.16. 3.17. 2.76. 1.04. 2.04. 1.98. 1.10. 1.77. 1.49. 1.51. 1.57. 1.79. 1.60. 1.22
Data Y:
7.79. 7.42. 8.48. 9.02. 8.09. 8.39. 8.41. 6.39. 6.92. 7.67. 8.06. 7.19. 7.23. 6.62. 9.14. 7.96
Data Z:
0.015231. 0.00494. 0.003793. 0.039367. 0.003723. 0.009354. 0.01030. 0.001494. 0.008419. 0.001878. 0.027863. 0.007789. 0.001448. 0.006181. 0.02448. 0.007942
R Code
(rho12 <- cor(x, y)) (rho23 <- cor(y, z)) (rho13 <- cor(x, z)) (rhoxy_z <- (rho12-(rho13*rho23))/(sqrt(1-(rho13*rho13)) * sqrt(1-(rho23*rho23)))) (rhoxz_y <- (rho13-(rho12*rho23))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho23*rho23)))) (rhoyz_x <- (rho23-(rho12*rho13))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho13*rho13)))) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson Product Moment Partial Correlation - Ungrouped Data',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistic',1,TRUE) a<-table.element(a,'Value',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation r(xy)',header=TRUE) a<-table.element(a,rho12) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Partial Correlation r(xy.z)',header=TRUE) a<-table.element(a,rhoxy_z) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation r(xz)',header=TRUE) a<-table.element(a,rho13) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Partial Correlation r(xz.y)',header=TRUE) a<-table.element(a,rhoxz_y) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation r(yz)',header=TRUE) a<-table.element(a,rho23) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Partial Correlation r(yz.x)',header=TRUE) a<-table.element(a,rhoyz_x) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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